• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.7-12
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• 1990

In this paper, we propose a new manipulator control scheme based on the CMAG neural network. The proposed control consists of two components. The feedforward component is an output of trained CMAC neural network and the feedback component is a modified sliding mode control. The CMAC accepts the position, velocity and acceleration of manipulator as input and outputs two values for the controller : One is the nominal torque used for feedforward compensation(M1 network) and the other is the inertia matrix related information used for the feedback component(M2 network). Since the used control algorithm guarantees the robust trajectory tracking in spite of modeling errors, the CMAC mapping errors due to the memory limitation are little worth consideration.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.358-363
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• 1987

It is widely noted that pressure feedback systems have been devised to damp the fluid resonance effectively in precision speed control-for large inertia system. A compensation technique preserving the natural output disturbance discrimination characteristics at lower frequencies is proposed The load pressure across positive displacement acceleration. The technique involves feeding back load differential pressure, sensed by pressure transducers, though a simple analog compensatory circuit (high pass filter). The effectiveness of the damping is determined by the filter time donstant and loop gain. Nonlinear total hydraulic simulation results verify the possibility of linear model predictions of extending the closed loop bandwidth beyond the uncompensated frequency.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.59-67
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• 2003

This paper presents a new approach for the use of smart materials, piezoelectric materials of PVDF and PZT, for vibration attenuation of a planar parallel manipulator. Since lightweight linkages of parallel manipulators deform under high acceleration/deceleration, an active damper is needed to attenuate vibration due to structural flexibility of linkages. Based on the dynamic model of a planar parallel manipulator, an active damping controller is developed, which consists of a PD feedback control scheme, applied to linear electrical motors, and a linear velocity feedback (L-type) scheme applied to either PVDF layer or PZT actuator(5). Simulation results show that piezoelectric materials yield good damping performance, resulting in precise manipulations of a planar parallel manipulator.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.4
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• pp.51-56
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• 2006

This paper proposes a control algorithm, which is verified experimentally, for aspherical surface grinding and polishing. The algorithm provides simultaneous control of the position and interpolation of an aspheric curve. The nonlinear formula for the tool position was derived from the aspheric equation and the shape of the tool. The function was partitioned at specific intervals and the control parameters were calculated at each control section. The position, acceleration, and velocity at each interval were updated during the process. A position error feedback was introduced using a rotary encoder. The feedback algorithm corrected the position error by increasing or decreasing the feed speed. In the experimental verification, a two-axis machine was controlled to track an aspherical surface using the proposed algorithm. The effects of the control and process parameters were monitored. The results demonstrated that the maximum tracking error with tuned parameters was at the submicron level for concave and convex surfaces.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.12
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• pp.2032-2038
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• 1989

Single mode optical fiber interferometeric sensors using phase tracking homodyne detection are typically susceptible to environmentally indured temperature fluctuations and other types of disturbances. A simple and effective phase tracking feedback electronic circuit for compensator is described to achieve stabilizing signal output, maximum sensitivity and linearity in the fiber optic Mach-Zehnder infterferometer in the presence of differential phase drift. The phase tracking range of the piezoelectric cyclinder in the reference arm is \ulcorner.7 \ulcornerad and the prabe mass about 1 gram in the sensing arm was used for measurements of the gravity acceleration.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.103-108
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• 2005

Loading/Unloading task in the real industry is performed by crane, but most of the loading/unloading task with the weight of 5kg∼30kg is done by human workers and this kind of work causes industrial disaster of workers. Therefore it is necessary to develop low cost loading/unloading manipulator system to prevent this kind of industrial accidents. This paper is concerned with the design and fabrication of 2 axis pneumatic manipulators using on/off solenoid valves and accurate position control without respect to the external load and low damping in the pneumatic rotary actuator. To overcome the change of external load, switching of control parameter using LVQNN (Learning Vector Quantization Neural Network) is newly applied, which estimates the external loads in the pneumatic cylinder. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied to the switching control system. The effectiveness of the proposed control algorithms are demonstrated through experiments of pneumatic cylinder with various loads.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.12
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• pp.176-184
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• 2000

TDC(Time Delay Control) deals with the time-varying system parameters, unknown dynamics and unexpected disturbances using time delay. TDC can be divided into two separate parts: an auxiliary controller and a servo controller. The two controllers can be designed independently. The auxiliary controller is used to reduce sensitivity to parameter variations, nonlinear effects, and other disturbances. The servo controller is to reduce the error between the desired command and output. We propose the model-following time delay controller with modified error feedback controller. This was applied to follow the desired reference model for the uncertain time-varying overhead crane. The model generates the damped-out swinging motion trajectory to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. The control performance was evaluated through simulations. The theoretical results indicate that this control method shows excellent performance to an overhead crane with the uncertain time-varying parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.6
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• pp.907-917
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• 1997

The purpose of this study is to design an anti-sway motion for industrial overhead cranes which transport objects on a horizontal plane by adjusting movements of a trolley motor and a girder motor. The movement of a hoist motor has not been considered at this time since its role was assumed to move objects only vertically, therefore, not to affect the swing motion of objects. The dynamic behavior of the swing motion shows nonlinear characteristics, which makes the design of anti-sway motion controller difficult. First of all, the nonlinear state equation for the motion of industrial overhead cranes has been derived. Then they have been linearized about normal operating states determined by the dynamic characteristics of motor motion-acceleration, constant speed, and deceleration, and deceleration, during transportation. The partial state feedback control algorithm based on this linearized state equation has been developed on order to suppress the swing motion. The simulation results have demonstrated satisfactory performance of the proposed controller.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.31-35
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• 1992

This paper presents a decentralized adaptive controller design for a robot manipulator to track the given desired trajectory in the joint space. The controller is of distributed structure and does not require the complex manipulator dynamic model, thereby it is computationally very efficient. Each joint is independently controlled by a PID feedback part and a velocity-acceleration feedforward part. Simulation results for a two-link direct drive manipulator conform that the proposed decentralized scheme is feasible.